Figure 1 from the paper. The island of Mahé with study sites and pollination networks (for more details see the paper itself).

Kat Raines

I chose this article as it merges my past and present research areas. I currently work in radioecology, focussing specifically on pollinators in Chernobyl but previously I worked for three years in the Seychelles archipelago on invasive species projects focussing on everything from plants to mammals. I thought this paper looked interesting (although slightly out of my research field) and attempted to answer some of the big questions relating to ecosystem restoration in response to the removal of invasive species.

The aim of this paper by Kaiser-Bunbury et al. is to examine whether ecosystem restoration through the clearing of invasive plant species affects pollination networks. This study was undertaken as a community field experiment on the island of Mahé, Seychelles. The Seychelles archipelago is ideal to conduct invasive species projects as it is relatively isolated from other islands and main land Africa and Mahé offers mid altitude inselbergs as discrete sites from which 8 were selected for this study. Half the inselberg sites were cleared of invasive species and therefore referred to as restored and compared to sites that had not been restored. They found that restoration markedly changed pollinator numbers, behaviour, performance and network structure.

The authors noted that the removal of dense thickets from the restored sites could have had an effect and we wondered exactly how much this would affect pollinator’s ability to even see flowers and whether it was then appropriate comparing sites with dense vegetation to sites with a greater number of clear areas therefore increasing the visibility of flowers.

This study found that interactions in restored networks were more generalised and therefore indicate higher functional redundancy therefore making these networks more robust. This concept was a main point in the discussion for the group as we debated whether it was better to have a high number of specialised pollinators or whether it was better to be more generalised and to what extent this matters on an isolated island with a high number of endemic species. It has been shown that specialist species suffer from habitat loss the most and tend to go extinct first whereas more generalised species are more robust therefore increasing the ecosystem’s resilience. We also wondered if these findings could be extrapolated and applied to other regions and habitats as increased pollinator interaction is obviously a very important outcome for ecosystem restoration.

In conclusion we enjoyed the paper and were impressed with the amount of effort that went into data collection for the plant-pollinator networks. Ecosystem restoration is a powerful tool in conservation but it is relatively unknown what the effects of restoration are on ecosystem functions so this paper is a notable addition to that knowledge base.

Figure 3 from the paper. Posterior distributions for paternity probabilities at the group level. Posterior distributions for the probabilities that fathers (at the group level) came from roosts in the (blue) upper-elevation, (yellow) mid-elevation and (green) low-elevation, and from (red) swarming sites. For (A) low-elevation offspring (the inset graph shows the Wharfedale roost posterior distributions in greater detail), and (B) mid-elevation offspring.

Following the last two discussions, this week’s paper was selected on the basis that it used non-lethal DNA collection techniques to determine how intra-specific niche separation influences mating patterns.

Matthew Guy

A large number of temperate bat species, including Myotis daubentonii, display sexual segregation along altitudinal gradients. In these species, mating usually occurs during autumn swarming events. However, at the upper limit of the female range, Senior et al. (2005), found evidence of summer mating within roosts where dominant males are tolerated by females. Using the same population of M. daubentonii, this paper extends this work to identify if this is the dominant mating strategy throughout the altitudinal range of the species and, if not, can the differences in mating strategy be explained by foraging habitat quality?

DNA was extracted from wing punches and a novel Bayesian approach was used to assign the probability of parentage of juveniles from low altitudinal roosts to males from different roosting sites and swarming sites. During our discussion, nobody had a lot of experience with the genetic methods used and we found the results section difficult to read. However, the figures clearly demonstrate that the probability that these juveniles are fathered by males from anywhere other than swarming sites is very low. We thought that this was a really nice example of how figures can be used to give a clear overall impression of complex data, especially for the lay person. This result was in contrast to that found by Senior et al. at mid-elevation roosts suggesting a flexible mating strategy over an altitudinal gradient.

Foraging habitat quality was assessed using bat activity, weight and temperature, all of which declined significantly with altitude. The paper surmises that by excluding males from roosts, pregnant and lactating females can reduce intra-specific competition for the high-quality foraging grounds. However, the carrying capacity at intermediate sites is lower and so supports fewer females. In these areas, the thermoregulatory benefits provided by males in the roost outweigh the costs incurred by additional competition. The paper pulls these results together qualitatively, stating that the mating strategy is adapted to the social structure, which, in turn has evolved in response to environmental conditions at a given altitude. However, we felt that an analysis of prevalent mating strategy (i.e. probability juveniles were fathered at swarming events) within individual roosts and local foraging habitat quality together would address the second part of the research question more directly.

Over all, we felt that the paper was well written and, in combination with the Senior et al. paper results, presented an interesting behavioural response. However, the scope of the paper is fairly limited, largely due to a combination of studying a single species and developing ideas of a previous single study. One potential way to widen the papers appeal could have been to incorporate a discussion on how the novel genetic technique developed in this study could be applied to other species populations.

The paper ends by posing the question: Is this flexible mating behaviour capable of dealing with changes in prey distribution and roost microclimate predicted by climate change? Our discussions came to the conclusion that climate change could cause a decrease in the success rate of mating during autumn swarming events, potentially reducing gene flow. An increase in temperature would drive prey species upstream, where the higher proportions of more turbulent water would reduce the quantity and quality of the forging grounds. This could lead to a reduction in females within local nursery roosts making them more reliant on males for roost thermoregulation, and hence, an increase in the prevalence of summer mating. We thought that actually addressing the question, at least to some extent, in the discussion would have made for interesting conclusion and again potentially widen the papers appeal.

This week’s journal club, whilst focussed on a single article, was also a chance for the group to have a wider discussion around the ethics of field work.

Historically much natural history research has been undertaken through ‘collecting’ specimens – i.e. killing and preserving individuals. The scientific descriptions of most species on the planet come from ‘type’ specimens held in museums; the individual(s) from which the species is defined and named. Early ornithologists went out birding with shotguns, not binoculars. However, in recent decades this view of biological science has been gradually replaced by non-lethal methods (such as camera-trapping, DNA analysis, radio-tracking, etc.) and the use of fatal collecting methods (certainly amongst vertebrates) is growing increasingly rare (aside from e.g. medical research, which I will not discuss here).

In this week’s paper, Costello et al. (all editors of the journal Biological Conservation, in which the paper is published) confront the ongoing issue of articles submitted to the journal that have, in their view, involved the unnecessary lethal collection of vertebrates, and have therefore been rejected for publication. The three recent examples that the authors discuss involved fish; in two instances researchers employed the use of gill-nets (which often lead to mortality of other non-target species as well), and in another there were very high rates of mortality due to tagging in a capture-release study. Importantly, in all instances the papers were not investigating a novel idea; instead they were simply showing well-understood phenomena in a different location. A table presenting a checklist of considerations for respectful conduct during field sampling highlights this as an important point; any negative impacts must be justifiable in terms of the advancement of scientific knowledge. However, as was pointed out in our debate on this paper, often it is not known what the results may be in advance of a study! Even fairly closely-related species can react very differently, and without first carrying out the field research this can’t necessarily be predicted.

Whilst lethal collecting or increased mortality due to methodology are the main topics, the paper discusses a number of other important issues surrounding field research. One of the first sections highlights the “uneven treatment of species”; and whether the relevant authorities (be they university ethics committees, or government officials) are more likely to allow lethal collection of one taxa over another. They ponder whether the case studies discussed involving fish would have been given permission had it been birds, mammals or reptiles involved – most likely not. This led to some discussion in the group about how much we understand about the way fish react to stimuli; a recent study looked at the use of compounds commonly used to euthanise laboratory zebrafish specimens, which was assumed to slowly send them to sleep. This compound was actually shown to drastically alter their behaviour prior to death, forcing the normally shade-seeking fish out into brightly lit areas of the tank. If this is the behavioural response, can we truly understand how the fish are reacting internally? And is it really as humane as was formerly thought?

Another important topic discussed within the paper was the impacts to non-target species that may result from any programme of fieldwork. This could include trampling (of vegetation or of e.g. invertebrates), or the transfer of invasive plant species or diseases (such as the fungus that causes white-nosed syndrome in North American bats, which has wiped out millions of individuals; the disease may have been inadvertently introduced by European-based cavers or bat ecologists).

The paper finished with a number of different solutions to the issues discussed. This included the use of low-impact methods where at all practicable, such as camera-traps, hair and faeces collection, drones, and observations. They also highlighted the importance of applying the ‘precautionary principle’ to research work, and to consider the possible impacts to the whole ecosystem being studied, not necessarily just the target species.

What is not really discussed in the paper is the perspective of different ‘types’ of researcher; for example a virologist may have a different view of lethal collecting to a conservation biologist. Another point that was brought up during our discussions, but is again not mentioned in the paper, is the cultural significance of certain organisms. Whilst a university ethics board may approve the lethal collection of a species, if it is viewed as particularly important, maybe even sacred, to native peoples in the study area, this should certainly be an important consideration for any researcher.

Whilst the paper is only three pages long, it succinctly covers a range of key considerations when planning any programme of field work. We concluded that this is an important paper to remind scientific researchers not just to fully explore all potential sampling methods before resorting to lethal collecting, but also to consider other potentially negative impacts that could be caused by the study. For example disturbance to other non-target organisms and the spreading of invasive species due to researcher movements should be considered prior to any research work. Whilst there were some comments that the paper may be viewed as a little ‘preaching to the converted’, the fact that multiple papers have been submitted to Biological Conservation that do not meet the ethical standards set by the journal highlights that it is still an important topic to discuss. This importance is highlighted by the fact that this article is one of the most downloaded from the journal in the last 90 days.

A few weeks ago Lynsey bribed me with some really very delicious cake to write a guest blog here. Well I say bribe, it’s quite an honour really, so I chose one of my all-time favourite papers that I consider a ‘classic’: Parmesan & Yohe ‘A globally coherent fingerprint of climate change impacts across natural systems’ published in Nature, 2003. This research ties together the differing ways of viewing the world of biologists and economists, to clearly show that there are systematic biological trends being caused by climate change: poleward range shifts averaging 6.1 km per decade (or meters per decade in altitude) and spring events coming in on average 2.3 days earlier per decade.

This paper was in answer to disagreements within the IPCC as to whether changes in biological systems could be attributed to climate change, or not. And what a way to answer! Parmesan & Yohe combine methodologies of biologists and economists – engaging both schools of thought – and analyse a comprehensive dataset on species ranges and phenology, across diverse taxa and regions, to find out if there is a general response of species to climate change. They do this using meta-analysis, categorical analysis and probabilistic modelling of range-boundary shifts in birds, butterflies, and alpine herbs; and phenology changes in herbs, shrubs, trees, birds, butterflies and amphibians.

So often you can get lost in the murk of confounding factors which obscure small changes in a species’ range or phenology, when looking at a single species or region. Land-use change for example has huge impacts on species, and its immediate effects could overshadow the small and long-term changes caused by a steadily changing climate. These small, niggling, persistent changes in ranges and phenology have the ability to fundamentally alter communities over hundreds of years, their interactions, and even cause biomes to shift position or switch from one type to another. A whole biome switching. Quite a thought. I like that Parmesan and Yohe have stepped back from the immediate – and granted very pressing causes for biological responses – to see big picture changes coming from tiny alterations in range and phenology year on year.

Given the impacts that climate change could have from local- to biome-scale, it still baffles me that there isn’t more action being taken to curb emissions and mitigate negative impacts of climate change sooner rather than later. Perhaps one of the reasons is because there isn’t enough interaction between researchers and policy makers, but papers like this one, which help improve dialogue between different the parties and provide a nice summary of evidence, are surely what’s needed.

My one gripe with this paper is the use of the term ‘global’ as in ‘global fingerprint’, and that’s because the majority of studies used in the analyses come from the temperate Northern hemisphere. This is because long and high-quality datasets come from here, but I wonder what would happen to the global fingerprint of climate change impacts identified if we added more studies from the Southern hemisphere, the poles, and the tropics. If there was more time, perhaps long-term data collectors could switch their biomes too.

Lynsey McInnes

So far, I am really enjoying the ‘classics’ angle we are running on PEGE as it gives me a chance to actually re-read (sometimes just read) papers with 1000s of citations and remember why they are so. While writing up my PhD, the contrary part of me used to hate citing the ‘most cited’ paper on a topic because I liked a diversity of citations. Hm. Sometimes classics are classics for a reason.

This is an awesome paper. You can almost hear the authors’ sighs as they sit down at the their desks, hands on table and decide – let us sort this shit out. Enough of people swinging this way and that, let’s compile the evidence and just let it speak for itself. Beautiful.

Saying that, I’m sure many people remain that are unwilling to be convinced by the weight of evidence presented or just don’t care. Their world view is such that any evidence for responses in other directions or greater risk or impact from other factors is enough to convince them that climate change doesn’t matter.

Beyond being staggered by the strength of the argument being portrayed here and the admirable way in which it was portrayed, here follows a selection of thoughts that popped into my head (yep, it’s one of those posts).

– I wonder how much bigger the dataset could be made today, 11 years on.
– I wonder (like Izzy) what the ‘answer’ would be if the dataset was more evenly global in scope.
– I wonder what’s going on with annoyingly small and difficult to sample biodiversity.
– I wonder how to put together P&Y take two where community/ecosystem wide responses are recorded to see whether these distributional and phenological shifts actually matter for ecosystem functioning (however you might like to define that).
– I wonder, if you didn’t care about conservation of species from a – they are here and morally should be saved – outlook, what shifts and losses really matter for ‘functioning.’
– I wonder what is really going to happen to high latitude regions which are set (at least sometimes) to gain biodiversity.
– I wonder if you could do a P&Y take 2b and identify a combined fingerprint of climate change and other threats such as fragmentation (probably not land use change – when its gone its gone after all).
– I wonder if this hybrid biological – economic approach is well suited in the debate on what ecosystem functioning is. Can economic theory and practices be put to good to use when quantifying what a functioning ecosystem is and how to keep it that way.

I think that’s enough for now before I get overly-philosophical. In short, I really, really enjoyed reading this paper for its measured, no nonsense approach to evidence. I don’t think it is the final word on people believing climate change affects species. It’d be great to hear what the authors think about the ensuring 11 years of research and whether we are anywhere closer to a. understanding what is going on and b. doing something (what?) about it.

Yes, I’m aware the above was a very ‘academic’ post – I’m sure I could enter the non-academic literature and find out answers to a lot (though probably not all) of the musings above. Maybe I will.

Will Pearse

This paper has been extremely influential, and I remember reading it in 2008 in my first undergrad conservation biology class. So I’d like to be self-indulgent and write about how my views on climate change have changed over the last few years. I’m no expert, so if you are you may well find what I have to say quite unsurprising.

The authors hope that if we measure enough things (range shifts), and then combine those things, we’ll understand more than if we just looked at each of those things separately. It isn’t helpful to ask whether each shift was ‘significant’ (…), we’re interested in drawing inferences about the total ‘population’ of range shifts, and getting a good sample of that. If that sounds controversial to you, think of it like this: if you were measuring the average length of toads, you wouldn’t ask whether a particular toad was significant, you’d measure a sample of them to make an inference about the single population from which those toads were drawn. Each measurement has very little information, but the whole is equal to the sum of its parts, and samples help us understand the population they’re taken from.

In biology, small changes add up in the long-run, and the authors focus a lot on the different time-scales in economics and the rest of the world. Discount rates have a rather profound effect on what is rational behaviour! However, we now know that it’s wrong to characterise climate change as a strong, steady force – that would be scary enough, but it’s much worse than that. As the climate shifts every aspect of it becomes more erratic and unpredictable, and the its rapid fluctuations indicate an impending catastrophic shift (that’s actually the technical term). When you undergo such a shift, pretty much all information you had about the system before is now worthless. You’re now drawing from a different population. Using observed range shifts now to measure shifts in the future assumes that the basic properties of the system will stay the same – and once we pass the tipping point, they won’t. Under the conditions we’re approaching, all bets are off. Frankly, if that doesn’t scare you, I don’t know what will.

Disturbance is a topic very close to my heart (that’s meant to be a physiology joke), mostly because I get very annoyed when people don’t define precisely what they mean by it. So I was very heartened to read this review, where the authors discuss the various temporal and spatial scales of disturbance, and also because it’s a very nicely written paper.

Disturbance, within certain conditions, can be part of the background homogeneity of a system, and the authors are keen to stress that in this paper. I was a little surprised to not find mention of the intermediate disturbance hypothesis (even though some find it controversial), since it’s so appropriate in this context. I found figure 1 (partially reproduced above), where the authors go through some case studies of what different kinds of disturbance look like, quite helpful in reminding me that disturbance can be lots of different things, and it can have lots of different effects (not always bad). However, that figure 1 is made up of case studies reflects our lack of a coherent framework to structure how we think about disturbance. Moreover, the right hand side of the figure (which I cropped out, sorry!) talks about two case studies that involve “metapopulation” and “patch dynamics”; this makes a lot of intuitive sense to me, but on reflection I find that kind of weird. Metapopulation theory is a concept humans have generated, it’s not a thing that biological systems recognise, and I think it might be better to categorise systems on the basis of properties they share rather than how we find it easiest to model them.

So what would such a categorisation look like? After reading this paper I think disturbance severity, duration, and extent (bear with me) are three important axes. With ‘extent’ I want to incorporate the ability to temporally and spatially escape a disturbance; spatially means whether the disturbance is everywhere and whether you can move to avoid it, and temporally that means whether the disturbance happens very often or very infrequently and would probably incorporate seed bank effects. I’m sorry ‘extent’ is such a poor descriptor; I’m decaffeinated and would appreciate better suggestions! I’ve very deliberately chosen to put space and time on the same axis; you might prefer to split them. You might also prefer to add predictability as another axis; I don’t, not because I don’t think it’s important, but because I think a system’s history (which, in turn, incorporates predictability) affects quite a lot and the other axes mostly capture what the system has been doing in the past. Not a lot about genetics in this post (sorry!), and instead a framework that almost certainly already exists somewhere and I’ve forgotten I’ve read it. Please do tell me where!

Lynsey McInnes

I had high hopes for this paper. I’m attracted to any paper that deals with intraspecific variation head-on and am well aware that intraspecfic variation affects and is affected by processes occurring on varying spatial and temporal scales. So, a paper dealing with how disturbance affects genetic diversity seemed right up my street. I was curious about the direction the paper would take as my feeling was genetic diversity is generally quite hard to measure particularly in non-equilibrium populations (such as those that have been disturbed) and assigning particular genetic signatures to historical events (‘disturbances’) is notoriously difficult as not only can a range of different events leave the same genetic signature, the same event can leave different signatures depending on the ecology and population structure of the species involved.

It was good for my ego to find that the authors largely confirmed my suspicions of these issues, but sad for the paper that there seems no easy way out.

It seems that the current state of understanding is that we live in an increasingly ‘disturbed’ world . Events such as tsunamis, fires and grazing impact nearby populations, reducing the number of individuals and thus most likely (at least) point estimates of genetic diversity and the challenge is to recognise the types of populations/species that will find recovery from such impacts difficult or impossible (if one is interested in conserving viable populations, otherwise all impacting populations are interesting, for instance, what kinds of species can you bombard with disturbances and they bounce right back to pre-disturbance levels of abundance and genetic diversity?). It seems however, that little research has focussed on the relationship between disturbance and genetic diversity and that there are many outstanding questions.

The second half of this paper gave a helpful overview of these outstanding questions and laid out some helpful ways forward. Namely, and understandably, the integration of multiple sources of data (event type, species’ traits, samples across the range and through time, etc.) will help to unravel the impact, or non impact, of putative disturbances on genetic diversity and, more importantly, what these effects mean for the longer term survival of species and/or communities. In fact, the paper lists FOURTEEN outstanding questions linking disturbance and genetic diversity and all of these are interesting. It would have been nice if these had been dealt with in more detail in the paper, perhaps focussing on a couple and on real routes forward to addressing them.

Maybe I missed this in the paper, but I also felt that what was missing was strong evidence that one expects any general link between disturbance and genetic diversity. As next gen sequencing gets cheaper and more accessible for non-model organisms, it will become trivial to look for these links, but, I feel, we need to know what we are looking for before we go looking for it. The general view is that more genetic diversity per population is better to ensure buffering against a variety of disturbances, but the authors show this is not always the case. Individuals can come from beyond the disturbance centre to make up for lost individuals and/or diversity. To predict this rescue effect one has to have a bigger picture encompassing knowledge of the genetic diversity of multiple populations within and beyond the disturbance centre. Are there enough individuals for recovery and do these individuals possess the desired adaptations? (So, I might differ from Will in thinking metapopulation theory might be helpful here).

I absolutely believe that intraspecific variation within and between populations in terms of genes and ecology must be considered if we hope to understand how populations will cope in the face of point disturbances and longer term environmental fluctuations. This paper drove home to me quite how difficult this endeavour is going to be.

I picked this paper because I attended the first half of a workshop based around these criteria at a recent restoration ecology conference. Frankly, I’m amazed by this paper because I would have said a Red List of ecosystems was impossible. There are immense technical challenges in not just putting together but implementing something like this, and it sends shivers down my spine imagining how heated the discussion over ecosystem definitions must have been. I’m going to start by discussing the criteria, and then discuss the next steps (and essentially recapitulate what I said at the workshop).

This isn’t just a theoretical paper, the authors have applied the criteria in the supplementary materials, and I’ve heard that training and classification is going on right now. The criteria seem, at times, somewhat arbitrary in terms of precise numbers, but the figures seem reasonable, the authors are aware of this, and I’m sure others would argue the same is true of the Red List of species. One thing I find interesting is the authors aim to prioritise biodiversity to give “conceptual clarity” over ecosystem function or services (albeit hoping saving biodiversity will save everything), yet (in my eyes) criterion D is essentially ecosystem function anyway. I think much of this draws back to the inherent difficult of defining what an ecosystem actually is; there is no analogue of ‘extinct in the wild’ in this listing framework, probably because a garden of species actively grown and maintained to have a similar composition to a natural state wouldn’t count as an ecosystem. An ecosystem is self-sustaining, and is defined as much by nutrient flow as by what form that nutrient is in at one time. Which is a long-winded way of saying I’m glad function was brought back into the criteria!

What amazed me at this workshop was that these criteria are not the end product for IUCN. They want to ensure that when the list is released, policy-makers will have a handbook to guide them through how to engage with local people on the ground and implement conservation initiatives that everyone agrees on – or, if it’s the choice of everyone involved, to simply let that ecosystem die. Personally, I think this is a task equal (if not greater) in magnitude to generating the Red List itself; libraries are filled with frameworks (e.g., MESMIS, IAD, and many more) and university departments and NGOs are stuffed full of people who have strong and differing opinions on how this could be done. The task, to me, sounds harder than writing a handbook for politicians on how to construct a Red List of ecosystems. That said, ensuring there is a framework in place such that this list isn’t simply thrown out with no regard as to the impact that Red Listing a place where people live is an extremely good idea. Which is a long-winded way of saying I’m glad they (and not me!) are trying, and good luck!

Lynsey McInnes

This is an absolute beast of a paper and, in fact, has enough going on in it to make up 10 or so meaty articles. Kudos to the authors for forcing everything into one, this action serves to underline that the setup is not just an academic exercise in classifying at risk ecosystems, but a feasible mechanism to bring that risk down.I’m glad Will gave us some background context to the paper, his post converted my sceptical first view of the paper considerably. Sure, there are a ton of authors here, but there’s also been a ton of work carried out.

Littered through my PEGE posts has been a nonchalent call to think more about ecosystems than about individual species, this is partly due to my lack of affection for a particular taxon, but also partly due to a belief, admittedly not rooted in much research, that ecosystems are a more useful unit for conservation than easy to delimit but hard to give equivalent value species.

So, I was initially disappointed that the authors chose ‘risks to biodiversity’ as their unit of risk assessment rather than some compound measure of risk to service or function. However, the authors do a good job of pointing out why this is the most feasible thing to do and flesh our their system more than enough for me to concede that this is probably a good idea and still, as Will says, captures functioning.

I alternately like and dislike the many similarities of the assessment criteria for ecosystems with the criteria for species (decline in distribution, etc.). The similarities probably aid focus and our ability to make the assessments, but I guess the worry is that they skirt around features of ecosystems that don’t have analogues in individual species. Saying that, their criteria to assess interactions, biotic and abiotic, probably covers much of these emergent ecosystem properties. So, really the authors probably have developed a comprehensive set of assessment criteria…

…the next step being the feasibility of implementing them and the uptake of doing something to curb impending ecosystem collapse when it is identified. Not a trivial undertaking one imagines!
How on earth does this happen? How many people (and cash) are needed to carry out these assessments? How do we prioritise which ecosystems to go for first (ones with the most data?, the most at risk?, the most pristine? an even geographic distribution?). Is the ultimate aim to cover all ecosystems? Which ones might fall through the gaps? Where do newly emerging urban ecosystems stand? Should stakeholders be able to ‘buy’ time on their favoured ecosystem? Its a minefield!

I have to admit I skimmed this paper way too fast, a lot of thought has gone into this framework, that is plain to see, and it looks like actions are already occurring in the ‘right’ direction. Let us hope that funding and/interest does not dwindle too soon.

I really enjoyed this paper because it falls exactly within three areas of conservation biology I am most interested in! Firstly, this paper addresses the age-old question of how much is enough to protect in order to achieve long-term species’ persistence. Specifically, it attempts to resolve the “SLOSS debate” which has been going on since the 1970s, with respect to whether Single Large or Several Small fragments are more effective for conserving biodiversity in a fragmented landscape. Rather than thinking about this question in a dichotomous manner, the authors conclude that the optimum variety of patch size and clustering depends very much on the individual species. This general finding is not novel, and it supports previous work on this topic, for example a paper by Nicol and Possingham (2010), who show that the optimum patch design for metapopulation restoration is heavily reliant on the metapopulation parameters themselves.

The authors do come to two very interesting, new conclusions. They use both mammalian metapopulation simulations and a real-world example to show that: a) having several small(er) patches is only beneficial when these are within 0.5-1.25 times the species’ maximum dispersal distance, and b) intermediate-sized species (~1kg) gain the most from reserve network clustering. These are very useful findings for conservation planning, and the authors discuss ways in which one could design reserve networks, while considering the optimum level of patch clustering for different sized-species. Their findings also touch on a second key point of interest to me, which has to do with evaluating the effectiveness of setting common persistence targets for conservation. This paper is a clear example of how important it is to evaluate whether species-specific goals could be more appropriate than applying blanket “rules of thumb”, which may not always be beneficial.

One point which I do not agree with in this paper is the authors’ conclusion that “network decisions should be made for the largest bodied species, as they will have the highest absolute extinction risk”. By basing network design on the largest species, wouldn’t this result in patches being too far away for many smaller (intermediate-sized) species to disperse to? This seems a little counterintuitive, especially since the intermediate-sized species were found to benefit the most from clustering. It would seem more appropriate to determine the patch distance and sizes which could result in the greatest overall reduction in extinction risk, across all the different species’ within the system. The costs of protection, as well as the likelihood of successful reserve network establishment are further factors that should be considered when drawing up such designs, which the authors do not mention.

The third area of conservation biology that this paper touches on, which interests me a lot, is their sophisticated metapopulation modelling to infer species’ extinction risk! The paper’s supplementary information has a very detailed description of the models, which could be a useful reference for anyone attempting a similar set-up. Although computationally complex, the authors candidly recognize the biological simplicity of their metapoulation models and landscape matrix, which could be perceived as a potential failing of this analysis. But I have to agree with them: there is always room for adding complexity, and it would be very interesting to test their method under further real-world situations, however, I do believe that the patterns they have found can provide a useful framework for conservation planning decisions.

So, overall, I found this paper very interesting! I would also like to give a heads-up to anyone who is interested in this topic that a colleague of mine at La Sapienza University in Rome (Luca Santini) is currently working on an analysis which reaches very similar conclusions, and his upcoming paper should be kept in mind as further support for these novel ideas.

Will Pearse

This paper dredged up all sorts of undergrad SLOSS (Single Large or Several Small) debate memories, which was fun! I enjoyed the paper, and think it makes the point that there’s probably no such thing as an optimal reserve for all species in an ecosystem very well.

The next two points are more suggestions for a follow-up study, they aren’t intended to be critical. I think any discussion of SLOSS needs to incorporate edge effects, whereby patches are less good at the edge and so smaller patches can be less suitable than we naively expect. However, edge effects might interact with species body size, and I wonder what effect that would have on this demonstration of interspecific variation based on species body mass. Moreover, while some of these analyses are conducted over an ’empirical’ landscape, my feeling is that variation in habitat quality and type among the patches is going to have a really big impact on reserve design.

I view the SLOSS debate as having come to an amicable truce now, in part because there is no one single answer. I don’t really think the authors are trying to give a single answer to this debate, rather they’re trying to give advice driven by this particular case study/modelling exercise. We need to shift what kinds of reserves we’re designing for depending on what we want to conserve, and I think allometric scaling seems like a pretty good way of doing that when we haven’t got the data on a particular species, although I’d want to ground-truth any proxies before relying on them too heavily. Maybe the best answer is a modelling exercise tailor-fitted to your own system!

Lynsey McInnes

I liked this paper a lot. It was an extremely well-written, balanced and useful advance within the reserve design literature that concluded there is no optimal design that will cover all, e.g., mammal species. This is because they have a ‘characteristic range’ related to their maximal dispersal distance which means that, effectively, small things can’t overcome interpatch distances beyond on a certain size. Sounds reasonable, but has rarely been shown in such a comprehensive, quantitative way.

The authors are very open about limitations, including the structure of their model, the homogeneity assumed between patches, the allometric relationship used to relate body size and dispersal distance, and so on. Their conclusions, though, should be more or less robust to these assumptions because the effect is overwhelming lydriven by dispersal ability.

I was really happy to read this quantitative assessment of an issue that seems to be typically approached in a very qualitative way, focussed on the largest species. I might have gotten confused, but I think the authors caution against this traditional approach as this biases design to large patches big enough for the largest of species and forgets about the right inter-patch distance for dispersal of a range of species.

Their conclusion that there is no optimal design is worrying. What additional factors could be included to get, at least a subjective, optimum? Perhaps some measure of function or phylogenetic ‘coverage’ or some other measure of health and/or endemicity of the species involved (ignore species that are screwed for other reasons, or found in good numbers elsewhere?). Like with the Joppa paper two weeks ago, including the economics of conservation might be useful too. Ooops, some of those might be construed as controversial, but at least might result in designs thought optimal, at least for some ends. Local optima?

I’ll end with a plug for a friend’s paper on mammalian dispersal distance. Whitmee and Orme conducted a thorough study to find robust predictors of dispersal ability for a painstakingly compiled database of mammalian dispersal distances. Merging it with the modelling framework set up in this paper might help us get one step further in designing good (lets avoid terms like best or optimal) networks for mammals.

This paper, which came out 3 weeks ago in Science, assesses the feasibility of the UN Convention on Biological Diversity’s (CBD) goals of protecting 17% of the terrestrial world and, through the Global Strategy for Plant Conservation, 60% of plant species. Using data from a large database of plant species distributions, they show that: a) it is physically possible to achieve these two goals simultaneously (because they were able to find a group of regions comprising 17% of the terrestrial world containing the entire ranges of 67% of plant species); and b) that regions with the most plant species have only slightly more area protected currently than those with fewer species.

I want to start by saying that I think this paper is an important advance in the ‘hotspots’ literature. It identifies regions of high diversity and endemism using an algorithm and data that are transparent and can be updated – an important step forward from previous frameworks based more heavily on expert opinions, as the authors point out.

However, I also feel I must briefly let my grumpy inner economist out of his cage, and reveal myself to the world as a big fan of Hugh Possingham, Steve Polasky, and others who have taken somewhat more pragmatic approaches to the problem of spatial conservation planning. While this paper does an excellent job assessing the physical feasibility of the CBD’s goals, I think it could have, without much extra work, gone much further in addressing other issues affecting the CBD’s practical feasibility.

In particular, I was very surprised to not see the words ‘cost’ or ‘economic’ anywhere in this paper (I even double checked this using command + F after I read through it the first time). As we all know well (e.g. McCarthy’s et al. 2012), conservation initiatives run on a highly limited budget worldwide. It is critical for spatial conservation planning to take this into account if protected areas are going to maximize the biodiversity protected. As a cartoon example, suppose a country has a billion dollars to spend on protected areas and must choose between protecting one area with 30 000 species at a cost of the full billion or two areas of equal size at 500 million each with 20 000 species each. The authors’ greedy algorithm would suggest protecting the first area (with 30 000 species), but more species (40 000) would be protected with the available budget if the cheaper, lower-diversity areas were protected instead. The authors remark that the areas with highest diversity identified by their analysis are not protected in practice much more commonly than areas with lower diversity. I wonder if these lower diversity areas are chosen because they are relatively cheap. The authors’ mention, in the middle column on page 1100, of a bias in protected areas towards high, cold, dry lands that are far from people seems to support this hypothesis.

To suggest that this paper should have formally addressed costs in its analysis is perhaps a bit unfair, as no paper can address everything. However, I do think the authors should have discussed them, even if only briefly. Moreover, I think incorporating costs into the conservation prioritization framework developed here is a highly fruitful area of further research. For example, this paper estimates the minimum area needed to preserve 60% of the world’s plant species. A future study might try to estimate the minimum cost of such conservation. The similar recent analysis by McCarthy et al. on birds provides one example of how this could be done. Combining spatial planning algorithms optimizing for minimum cost and minimum area could yield estimates of an efficiency frontier balancing the two that would be highly useful for policy-makers and spatial planners (see Polasky et al. 2008 for an example of a similar analysis). Some research groups, notably Hugh Possingham’s (I told you I was a fan), have actually already made some promising strides in this direction (e.g. Wilson et al. 2006). I was also quite surprised to not see this or other similar studies cited or discussed by Joppa et al.

I apologize for this somewhat long-winded post, but to conclude, I think this is a good paper that, with a little bit more analysis or discussion of costs, could have been a classic. Nonetheless, I think this study lays the foundation for tremendously fruitful further research in spatial conservation planning.

Will Pearse

I have a dirty secret: I love hotspot papers. I love staring at figures like the one above, and thinking about how we live in a world where we can pinpoint where all the world’s diversity is. So bear that in mind.

I think Matt unleashed his grumpy economist a little too early. This is a great hotspot paper. The authors use fundamental biogeographical theory to show why regional data are untrustworthy; I don’t care what form you think the species-area relationship takes, that one exists means the resolution at which the data were collected matters. Yes, there is no explicit costing in this paper, but that is not the point of it – the paper is trying to make a map of endemism, and I think they do a pretty damn good job of it. Although I have serious issues with using endemism as a conservation prioritisation tool, Red Listing all these species would take far too long and so this is probably the best we can do. This is not a paper that is aiming to come up with a robust (economic) prioritisation of the world’s flora, this is a hotspot paper that is trying to figure out where things are and point out the areas of a priori importance. I think Lynsey (below) is right in pointing out that we have a lot of papers like this (here’s another relevant one), and maps of the world’s phyogenetic diversity are beginning to emerge. Indeed, figure 2 plots the number of species protected under various schemes: since we first have to establish whether the species in protected areas would survive without them, and also how much we value those species, I’m not sure what we can do with graphs like this.

The deeper question I think we can all ask is why we need papers like this, and why we shouldn’t just all be out in the field waving placards and setting up reserves. To answer that, I want to talk about when I (briefly) met Lucas Joppa (I think) and Stuart Pimm while doing my MSc at Silwood Park. Felix Whitton and I were running a conservation news website (Conservation Today; the site is dead but check out these talks), and Pimm gave us a ~two hour interview. I specifically remember Pimm saying that it was more important to worry about what was going on “at the coal face” than spend your time making hotspot maps of the world. So why one more hotspot paper for him? Because papers like this give conservation NGOs easy-to-interpret guides (“have you thought about parks in this country, because they have a load of endemics”), and give us an opening to get more money (“hey *insert name of rich person*, this easy-to-understand map that was published in Science says we need more parks here!”). Pimm and others are out there trying to get money to get things saved, and papers like this help them. Fundamentally, it’s not the economic efficiency of a park system that saves wildlife, it’s the product of economic efficiency and the money available.

Lynsey McInnes

Another permutation of sub-optimal range data, area-selection algorithms and conservation prioritisation! Rejoice! In all honesty, I wanted to dislike this paper as I feel we are all really going round in circles with these kinds of analyses, but there are things to like in this paper and things to ponder. I also love the style of Joppa, Jenkins et al. (check out this PNAS paper, they are just cutting about other methodologies in a way that is simply fun to read).

Anyways, I am fairly sure that Matt is going to focus on the economic (un)feasability of their conservation guidelines, so I will skip that side of things altogether.

I like that they take actual established guidelines for protected areas and numbers of plant species that need protecting and try and work back from there to establish if they can find the optimal areas that would cover these species numbers in the minimum possible areas. They then show there is substantial overlap with restricted range vertebrate species. All it,well and good. Again, ignoring the economic and political side of protected area designation, do these results tell us much we didn’t know already. A bit…

My biggest concern, and this goes for most such studies, is do we really just want to protect areas with high numbers of species? Don’t we want to conserve ecosystem function or phylogenetic diversity (i.e. a variety of species and a source of new ones)? Don’t we want to make sure that there are corridors for species’ movement and that protected areas are well-connected and likely to be useful in the future? Don’t we want to square conservation goals with existing landuse scenarios and development goals? I am of the opinion that Myers’ hotspots were profoundly important in identifying to scientists and the general public that there are regions with there is a ton more biodiversity than elsewhere, that these are typically beautiful, interesting and probably contain a lot of tapped and untapped resources. Everything since then has (really) just reinforced his original set, perhaps adding a couple more outliers, or more pristine habitats that didn’t make his cut because they hadn’t been screwed up yet. But really tropical areas, islands, some outlier temperate areas are always identified. If you change your criteria, you might get a high latitude region or two. Where do we really want to go from here?

I would say, let’s get campaigning and conserving. Let’s get action happening to protect at least some of these amazing places. Let’s work out what is feasible (politically and economically) and get going.

This paper, which came out in February in Science, received what I would describe as strongly mixed reactions, particularly among economists. In my opinion, many of the negative reactions to this paper are ultimately traceable to the fact that it is misclassified by Science as a Research Article when it is really more of a review. Perhaps in the spirit of this masquerade, it also introduces some superfluous mathematical models that are scantily developed and mostly unnecessary to make the authors’ points. Nonetheless, I think this paper is worth reading, particularly for non-economists interested in environmental and development issues, as it gives one of the more accessible overviews of the concept of externalities I have read, and does an excellent job of highlighting examples of externalities relevant to sustainable development that are not widely appreciated.

In case the banking crisis of 2008 (not to mention the Great Depression) wasn’t evidence enough, it turns out that markets don’t always work well to produce efficient outcomes for society, despite what some libertarians might have you believe. Economists have a precise definition of ‘efficiency’: A particular outcome, X, is ‘efficient’ if no other outcome can be achieved with the same resources in which all stakeholders are at least as well off as they are in X, and at least one stakeholder is better off than they were in X. Though some early economic theories hypothesized that free markets should lead to efficient outcomes, many examples of ‘market failures’ – situations in which free markets failed to produce efficient outcomes – soon emerged.

Externalities are some of the most common causes of market failure. Externalities are consequences of decisions for others that are unaccounted for by the decision-makers. The ‘tragedy of the commons’ is the quintessential example of inefficiency caused by externalities. As a quick cartoon example of the tragedy of the commons, suppose citizens of a city are trying to decide how much to spend on building and maintaining public parks. Each dollar any particular citizen spends on parks provides a benefit of X to both them and each other person in the city, and each dollar a citizen spends on their own private consumption gives them (and them only) a larger benefit, Y (i.e. Y > X). If each citizen decides privately how they want to spend their money, no one will spend anything on parks because, no matter what other people spend on parks or how many other people there are, the benefit to a particular person of spending an additional dollar on private consumption (Y) is always larger than the benefit of spending the same dollar on parks (X). However, as long as the number of people in the city is larger than Y/X, each person would be better off if everyone spent all their money on parks than if everyone spent all their money on private consumption. Thus, the outcome produced by a ‘free-market’ (no parks) is inefficient (provided the number of citizens is greater than Y/X). The externality in this example is the benefit a particular citizen’s money spent on parks has on the other citizens, as this does not get accounted for in the citizen’s private decision on where to spend their money. This externality is what causes the free market outcome (where everyone privately decides how to spend their money) to be inefficient.

There are many well-known examples of externalities leading to adverse environmental impacts and the degradation of natural capital. For example, fisheries are often overexploited because each fisher’s fishing effort reduces the future revenues of both them and other fishers by depleting the stock. This leads to a race for fish among the different fishers, resulting in the overexploitation of the stock. Similarly, companies’ choices to pollute generally don’t consider the negative impacts of the pollution on other stakeholders. This externality leads to higher pollution levels and is a significant obstacle to climate change mitigation.

Dasgupta and Ehrlich highlight some examples of externalities leading to increases in consumption and population growth in this paper that are not as widely appreciated. For example, they discuss how fosterage (sharing of parenting responsibilities among members of extended families or communities) and low paternal investments in parts of sub-Saharan Africa lead to increased fertility rates. The externalities here are the costs of parenting not borne by the parents themselves, and thus potentially unaccounted for in their decision to have additional children. Two general sources of externalities the authors highlight are social conformism and competition. If people have a desire for their reproductive or consumption decisions to conform to the decisions of others, then the private consumption and family planning choices each person makes have impacts unaccounted for (i.e. externalities) on the choices of others. Thus, if everyone is consuming or reproducing a lot, any one person would not be inclined to consume less, even if it was better for them otherwise (e.g. economically). If people consume competitively (e.g. if consuming more than others confers high social status), then each person’s decision to consume more also has unaccounted for effects on the consumption of others, which can cause people to consume more than might otherwise be in their best interest.

Two of the authors’ main conclusions seem to be that externalities at the population-consumption-environment nexus i) present significant challenges for policy, and ii) can result in positive feedback spirals leading to rapid increases in environmental degradation. Races among individuals to consume more (resulting from competitive consumption) or to extract shared resources are examples of such spirals. On the policy side, one point I think they could have made more clearly is that inefficiencies caused by externalities can generally only be overcome by some type of cooperative decision-making at a (geospatial, social, temporal) scale at least as large as the externality itself. This means, for example, that externalities exacerbating climate change likely require global cooperation to overcome. Given the large spatial and temporal scales of many of the environmental externalities, and the increasing geospatial scales of many consumption externalities as a result of globalization, strengthening global cooperation on environmental issues may be one of the most pressing challenges of our time.

Overall, I like this paper, despite the fact that I think it overstates its novelty and introduces superfluous math. I agree with the authors that externalities pervade many facets of human consumptive, reproductive and environmental decisions, and pose serious challenges to sustainable development. There is a very rich literature in economics and political science on externalities and the institutions needed to overcome them, which I encourage any others who enjoyed this paper to dig into.

Will Pearse

I started thinking a little more seriously about sustainability and economics a little while ago, and so I enjoyed reading this paper as it gave me an opportunity to load up those parts of my brain again. However, I’m still wildly out of my comfort zone with this paper.

Matt mentioned this is more of a review; I’d say it’s more of an essay, and it is an essay I enjoyed very much. I think the general point that cultural systems can drag us further down the route of unsustainability, and that these can be thought of in terms of externalities, is a novel and nice one. I suppose my only problem is I’m not sure how we can move forward and use this framework to help tackle issues. Figure 1 (which is reproduced above) demonstrates my point quite well – all three of these boxes (population, consumption, environment) are linked, and they all affect one-another. I’m not very good with flow-charts, but I find frameworks where all the boxes are linked unappealing because it doesn’t help me break the issue down into sub-components that I can assess, which is exactly the kind of over-simplification I want in order to help me visualise a system. Equally, I find all of the authors’ points compelling, but I’m not sure they give me any pointers as to what new things we should be focusing on in order to fix problems. All of these criticisms are of course unfair, since the first outing of a conceptual framework is hardly going to cover ever conceivable question anyone can have.

I did find the idea that economists have viewed natural capital as inexhaustible interesting. Many of the papers I’ve read (Kenneth Arrow, please take a bow) do recognise that nature is finite, and have put together whole frameworks with that in mind. Indeed, I thought the whole peak oil debate was very much well-known by economists! Maybe there’s a parallel with the non-linear dynamics that Dasgupta and Ehrlich discuss and the uptake of those ideas into biology; several fields (limnology springs to mind) have been well-aware of non-linearities and tipping points in ecological systems, but the rest of ecology seems to have been slower to get on-board. If this paper is bringing together previously un-linked fields of economics under a new framework to look at these issues, then I hope lots of people read it!

Lynsey McInnes

When Matt suggested this Dasgupta paper I was excited because I’d just started reading ‘A very short introduction to economics’ written by Dasgupta himself. I think my nascent interest in economics comes from a long commute that means I’m much more up to date with current affairs than usual and it turns out the world is in a state. Why?

To be honest, despite ploughing through the first three chapters of my new book, I was still a bit out of my depth with this paper, it could definitely have done with more figures, at least figures of the curves represented by their impenetrable equations. Nevertheless, it was a thoughtful piece especially to a biologist with little to no experience with what is undoubtedly a vast economics literature.

In short, it seems we are a bit screwed because of people’s innate desire to both conform to and be competitive with one another. This initially seems oxymoronic but conforming to competitiveness does kind of make sense. Basically, people have too many kids and eat too much so they ‘stay in the game.’ These behaviours continue because when people weigh up the consequences of their decisions they don’t think how they might impact people and entities external from their immediate unit (‘externalities’). Depressing.

The biggest worry, and the one that Matt explains even better than Dasgupta and Ehrlich, is that as the world becomes more connected, such that these externalities have wider and wider reach, the solutions similarly become more global and this, without much thought, is problematic.

The authors end on a fairly down note that we are spiralling along a route that is totally unsustainable (economically, socially, environmentally, ecologically) and being economists (at least Dasgupta) they don’t even give a falsely optimistic final sentence. What is going to happen unless collaboration and cooperation take root on a global scale pretty damn soon. Is there any likelihood of this kind of cooperation happening? There are plenty of global institutions, but they don’t seem able to penetrate all the places they need to and there seems to be geographical mismatch in places where behaviours need to change versus places where that change will impact.

It might just be me, but I like the cold hard mathematical approach to sustainabilty outlined in this paper. I don’t know whether a good to start to influencing behaviours is to confront the public or local and national institutions with more cold, hard facts or to spend more time trying to work out the biological/psychological underpinnings of destructive behaviours. Probably both.

The next generation of conservation scientists mix social, ecological and economic approaches to understand how human behaviours and population dynamics interact to generate species of conservation concern or conservation successes. But really this seems like a tiny field in relation to sustainability more generally. Is it a good case study to roll out more widely? (Might just be the one I know most about).It’s pretty obvious I don’t know much about this field, but it does feel weird to call it a ‘field’ when surely sustainability of the world’s population is the basis of, well, everything. And yet, frankly, I’m not going to give up my forays into pop gen to save the world, why?

If I take one thing away from reading this paper and writing down this jumble of thoughts is that solutions come from integration, we need the cold, hard numbers, but also cultural and societal insights, understanding of the motivations behind specific behaviours, and an outlook that is temporally and spatially broad. I would also argue for greater regulation, not less, but tempered with an understanding or just some foresight into how those being regulated will respond (just like we model how populations respond to management decisions). We’re still just another species after all.

And there ends the unqualified ramble into economic theory for this week.

Do you have a niche syndrome? You can get a cream for that you know… From Sax et al. (joke from Sarah!)

Sarah Whitmee

I chose this paper before I knew that Lynsey and Will were to review a very similar one just two weeks earlier, coincidence or something more sinister? Actually, I don’t think either of those things, but is in fact due to a new phase in the field of species distribution modelling (SDM), one in which concepts are clarified and the assumptions of models are questioned and tested. Well that’s my hope anyway…. Nevertheless, it is becoming increasingly clear that a big assumption made by those practicing the dark art of SDM, namely a linear relationship between the realised niche (the area of environmental space actually occupied by a species) and the true environmental tolerance limits of a species does not exist, at least not for most species. This was illustrated in the Araujo et al study discussed here, where it was neatly demonstrated that lower thermal tolerances varied widely across species while upper tolerances were much more conserved. Happily, I think this study complements the earlier paper, phew!

The authors start in true TREE style with a nice overview of the current state of the field and the definitions of key terms. While often this is just restating the obvious it’s actually a pretty useful exercise for anyone working in SDM to go through, varying definitions of the fundamental, realized and potential niche plague the discipline and formally stating them for yourself can help later down the line when trying to interpret and understand models.

They then get down to the business end of the paper, the introduction of a new concept: the ‘tolerance niche’. The tolerance niche is defined as “the set of physical conditions and resources that allow individuals to live and grow, but preclude a species from establishing self-sustaining populations”. While I’m not convinced that the field of species distribution modelling needs more jargon I can see the usefulness of this concept in theory, specifically in relation to predicting the impacts of climate change on species persistence. The idea is that while a species cannot thrive in these tolerance zones they can persist temporarily in them, for example during dispersal to reach new suitable climates or to outlast temporary climate fluctuations. The introduced concept is then used to illustrate a number of niche syndromes, or ways we might want to think about species responses under climate change. They choose horticultural plants as a key group for illustrating how you could formulate hypotheses for these niche syndromes and also how you might work out a species tolerance niche, from evidence of specimens in botanic gardens outside a species native distribution.

Overall I like this paper, its clear and well thought through. I buy into the idea of the tolerance niche and think it’s a good step towards more dynamic species distribution models, rather than the time-slice approach employed in earlier analyses. Being a macroecologist I have a problem with this paper that I often encounter with the more fine scale SDM work. While the concept or model works well for a single species or a particularly well studied ecosystem (its no coincidence that a large proportion of SDM studies are all about the South African fynbos you know) these concepts fall down due to a lack of data when you try to scale up for multi-species predictions. The example species given in the paper works beautifully for the concept they are proposing but I wonder how many other species show such clear relationships. So I would have like to have seen more real world examples to convince me that the tolerance niche can truly be estimated. I know very little about plants (outside the ones in my garden) but I’m nervous about the idea of inferring tolerance simply from presence in a botanic garden outside the native distribution with a better understanding of how the plant is managed in situ for example it might be protected against winter frost or supplemented with food or key nutrients. I guess for species of key conservation concern such an approach might pay dividends.

I did like the idea of managed relocation for slow growing species, putting them in an area that they can tolerate in the short-term but which will eventually become climatically suitable for growth and reproduction. It’s a risky business though and I would want a much higher confidence in my climate models before attempting such a bold step.

To sum up the tolerance niche is a neat concept but how applicable it will be in the long term, I’m not sure. I’m a fan of these authors though so perhaps other will have a different view.

Will Pearse

Like Sarah, I like these authors (and I know Lynsey does too!), so perhaps this is going to be a bit of a biased PEGE. I view the essential idea of this paper as defining the idea of a tolerance niche: conditions where a species can just-about survive, but can’t form a self-sustaining population. I buy it, and think it’s a nice idea and a great paper.

Indeed, I think similar ideas have been floating around in population biology for some time. We have source populations, that fire off propagules into the meta-community, and sink populations, where propagules arrive, individuals persist, but there’s a net loss of individuals and so that population can’t sustain itself. These concepts have really helped population biologists think about meta-community dynamics, and as we try to link macroecology more intimately with local-scale abundance changes and interactions, it seems sensible to conceptually link these concepts.

I wonder if we can go a step further, and stop treating different parts of the niche (fundamental, realised, tolerance, etc.) as discrete boundaries, and instead be up-front in acknowledging that we know species do better in certain parts of their niche than others, and maybe try to quantify that. Essentially, just have some value (why not fitness) that changes throughout niche space, and acknowledge that, in some parts of niche space, fitness will be so low that a population won’t be sustaining. Indeed, such an approach (borrowing heavily from Chesson) would let us handle realised vs. fundamental in a much more intuitive way, because we could distinguish between niche differences and fitness differences when trying to understand whether species can coexist. Because, as I’m sure we can all agree, parameterising a fitness function across niche space would be really, really tractable and easy to do :p

Hopefully the above makes sense; I have a very serious case of man flu!

Lynsey McInnes

This paper touches on plenty of topics that we have covered in different guises here at PEGE, with a perhaps more applied angle than most. In essence, the authors seem to be drawing attention to the potential importance of a kind of buffer zone of conditions that species could survive in beyond their current distributional limits (the tolerance niche) and how this zone might be extremely important in mitigating climate change induced species’ disasters.

The idea seems pretty reasonable and meshes well with experimental studies that find that translated populations can make it in conditions not found anywhere within their range. The authors also showcase a brilliant dataset of naturalised and garden centre/botanical garden populations of a plant species in the eastern US. The inclusion of this data lifts the paper from one based on loose concepts to one with real results; that was nice!

However, I do still worry how ‘useful’ the concept of a tolerance niche is going to be beyond these plant examples. In effect, the authors are creating an additional category of niche that in most cases is going to be quite difficult to identify? I would have liked to have seen one additional step to go the figure one and that would be to investigate traits that predict the extent and/or location of this tolerance niche. For instance, the authors draw attention to the distinction between short- and long-lived species, but are there any other distinguishing features? These could be along the lines perhaps of large range (probably also has a bit of tolerance niche), restricted range endemic (probably doesn’t), is part of a complicated food web (probably doesn’t have much of a tolerance niche), most kinds of generalist (probably do have tolerance niches). The next step, as the authors emphasise, is where is the tolerance niche located in relation to the realised niche and how easy is it to get to?

The above just gave me the nagging feeling that the tolerance niche concept might be quite difficult to implement as, like everything macro- it seems (I’m having a down on general patterns week), these things depend on so many other things: landscape structure, biotic interactions, the usual suspects. So, while the concept of the tolerance niche could provide US with a kind of buffer so that we can worry less about species’ survival (they can probably tolerate a bit more heat, drought, what have you) than they currently do, it seems like a difficult concept to draw strong or helpful conclusions from across broad taxonomic or spatial scales.

In conclusion, this was a well-written, thoughtful paper, but I am not convinced that the new concept and piece of jargon are robust or flexible (can something actually ever be robust and flexible?) enough to be rolled out very widely. As always, its a data problem…